In contrast to what many people think, Big Data and Hadoop are not the same things. The difference between the two is a fundamental one. The former is an asset whereas the latter is an open source software programme handling the asset – big data.

Big data is often a complex and equivocal in nature while Hadoop is a tool which consummates a set of goals and objectives for dealing with Big data. Let us try to understand what is big data and Hadoop and the difference and relationship between them.

What is Big Data?

Big data is nothing but the large set of data that is produced by different parties (it can be a business, social media, etc.) to serve particular operations and goals. It can include many different kinds of data in several formats. For instance, a party might put many efforts in collecting a large number of pieces of data on transaction of commercial vehicles formats and the costumer’s information like their name, Adhar number or the product information in the form of model numbers, sales information, etc. All of this data or any other large information can be called big data. The content stored is generally in Terabytes and Petabytes. Big data is generally unsorted and raw, until processed by specialized tools and handlers.

What is Hadoop?

Hadoop is one of the tools designed to handle big data. It is primarily used for analytics. Hadoop is built to process the big data searches through specific algorithms and methods. It not only processes big data but is also involved in processing various kinds of data – unstructured data, semi-structured data and structured data.

It is an open source program maintained by a global community of users and is registered under Apache license. MapReduce set of functions and Hadoop distribution file system (HDFS) are few of the main components of the Hadoop tool. MapReduce first maps the data and then reduces it as per the required command. It works like filtering a raw data. While HDFS distributes data across the network and moves it as per the requirement. Different features of Hadoop can be used by database developers, administers amongst others to deal with big data in many ways including clustering and targeting non uniform data, etc.

How Big Data Hadoop certification can boost up your career aspirations?

With the rapid digitalization of the globe, there is an increase in the big data production. There is a huge demand for Data Analytics in the companies. Companies are ready to pay big paycheques to rightly skilled and qualified professionals in big data analytics. According to Forbes, the number of data science and analytics jobs are projected to grow by nearly 364,000 listing to approximately 2,720,000 by 2020. Almost all the major sectors today are involved in using big data analytics, be it Baking and securities, sports, communication and media, healthcare and pharmaceuticals, manufacturing, insurance, etc. This is the right time for you if you want to enter the promising world of big data and become a big data Hadoop analyst. TeachingKrow offers a comprehensive online Big Data Hadoop certification programme. The company’s certification programme comprises of MapReduce, Hive, HBase, Pig, Flume, Sqoop, and HDFS architecture, the module offers an overall in-depth knowledge about Hadoop and its applications.

Though there are no prerequisites for joining the course, prior knowledge of SQL and Java helps in understanding the concepts. With 24*7 access to course material for comfortable learning, live interactions via virtual classroom remove the hurdles of accessibility and long travel hours. In addition, TeachingKrow practice tests also offer sectional analysis for identifying weak areas.



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